BMC Artificial Intelligence is calling for submissions to our Collection, AI in radiology: revolutionizing medical imaging and interpretation.
The integration of artificial intelligence (AI) in radiology has transformed the landscape of medical imaging and interpretation. AI-powered algorithms and machine learning techniques are being increasingly used to enhance diagnostic accuracy, automate image interpretation, and optimize radiology workflows. These advancements have the potential to revolutionize clinical practice, improve patient outcomes, and streamline healthcare delivery.
It is crucial for us to continue advancing our collective understanding in this area to harness the full potential of AI in radiology. Recent advances have demonstrated the efficacy of AI in detecting abnormalities in medical images, extracting imaging biomarkers, and facilitating rapid and precise diagnosis. Furthermore, AI has shown promise in improving the efficiency of radiology workflows, reducing interpretation times, and enhancing the overall quality of patient care.
We invite contributions that examine a wide range of topics relating to the application of AI in radiology, including but not limited to:
- AI-powered diagnosis in radiology
- Imaging data analysis using machine learning
- Radiology workflow optimization with AI
- Automated image interpretation and diagnostic support
- AI applications in medical imaging technology
- AI-driven innovations in radiology equipment
- AI-based solutions for personalized medicine
- Ethical considerations in AI integration in radiology
Please email Alison Cuff, the editor for BMC Artificial Intelligence, ([email protected]) if you would like more information before you submit.
This Collection supports and amplifies research related to SDG 3: Good Health & Well-Being, SDG 9: Industry, Innovation & Infrastructure.
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